DISSERTATION RESEARCH: Genetic architecture and evolution of reproductive isolation in Lycaeides butterflies

当不同的进化谱系在地理上接触并有机会杂交时，它们往往保持不同，因为遗传差异降低了谱系之间成功交配的概率或降低了杂交后代的适应性。物种形成是谱系分化和生殖隔离的过程，是生物多样性积累的基础。对物种形成的完整理解需要了解生殖隔离的遗传基础和进化。这项研究将揭示灰蝶和灰蝶生殖隔离的遗传基础和进化过程。梅丽莎这项研究的目的是确定这些物种的遗传区域的数量，分布和影响，以及自然选择在其分歧中的作用。与生殖隔离相关的遗传区域将使用新的统计分析，在两个物种之间的杂交种群的基因流。这些遗传区域将与在地理上孤立的种群中显示自然选择证据的区域进行对比，该项目将深入了解生殖隔离的遗传基础和自然选择在物种形成过程中的作用。该项目将进一步发展进化遗传学的统计方法，并将作为计算机软件提供给科学界。本科生和K-12教师参与研究将是一个优先事项，将涉及与怀俄明州夏季生物信息学计划的参与者进行计算工作，并与当地教师进行实地考察。

Where divergent evolutionary lineages come into geographic contact and have the opportunity to interbreed, they often remain distinct because of genetic differences that reduce the probability of successful mating between lineages or reduce the fitness of hybrid offspring. Speciation is the process by which lineages diverge and become reproductively isolated and is the basis for the accumulation of biodiversity. A complete understanding of speciation requires knowledge of the genetic basis and evolution of reproductive isolation. The proposed research will characterize the genetic basis and evolution of reproductive isolation between the butterfly species Lycaeides idas and L. melissa. The goals of this research are to determine the number, distribution, and effects of genetic regions isolating these species, and the role of natural selection in their divergence. Genetic regions associated with reproductive isolation will be identified using novel statistical analyses of gene flow in populations with hybrids between the two species. These genetic regions will then be contrasted with regions showing evidence of natural selection in geographically isolated populations.This project will provide insight into the genetic basis of reproductive isolation and the role of natural selection in the speciation process. The project will further develop statistical methods for evolutionary genetics, which will be made available to the scientific community as computer software. Participation of undergraduates and K-12 teachers in the research will be a priority and will involve computational work with participants in the University of Wyoming summer bioinformatics program and fieldwork with local teachers.